An Analysis of NBA Player Performance Using Principal Component Analysis

Introduction

• What is principal component analysis (PCA)?
• What dataset is being used?

Methods: Linear Combinations

• Principal component analysis reduces the dimensionality of data sets
• Multiple dimensions can be turned into a linear combination
• The linear combination is a unit vector, or a vector of length 1
• Multiple principal components can be represented on a coordinate plane

Data: Correlation Matrix

Data: Best Performers

Data: Best Performers

Data: Best Performers

Analysis: Eigenvalues

Analysis: What Makes Each PC

Analysis: What Makes Each PC

Analysis: What Makes Each PC

Analysis: What Makes Each PC

Analysis: Which Players Contribute Most

Analysis: Which Players Contribute Most

Analysis: Which Players Contribute Most

Analysis: Which Players Contribute Most

Analysis: Variables

Analysis: Biplot

Analysis: Players Overlay